Based on the locations of several unmanned aerial vehicles (UAVs) and their relative distances from a target, a ground target cooperative geometric localization method that is more effective than a traditional approach is proposed in this paper. First, an algorithm for determining the location of the target is described. The effectiveness and suitability of the proposed algorithm are then shown. Next, to investigate the location accuracy of the proposed method, the influence of three critical factors, namely, the flight altitude, UAV position errors, and measurement errors, is analyzed. Furthermore, for the required location accuracy, the feasible regions of these factors are determined based on their influence, and the location accuracy will satisfy the requirements if all factors are within the feasible regions. Finally, simulation results from the MATLAB/Simulink toolbox are presented to show the effectiveness of the proposed method and the availability of the feasible regions.
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Li P, Yu X, Peng X Y, et al. Fault-tolerant cooperative control for multiple UAVs based on sliding mode techniques. Sci China Inf Sci, 2017, 60: 070204
Zhang Y Z, Hu B, Li J W, et al. UAV multi-mission reconnaissance decision-making under uncertainty environment. J Northwestern Polytechnical Univ, 2016, 34: 1028–1034
He W, Huang H, Chen Y, et al. Development of an autonomous flapping-wing aerial vehicle. Sci China Inf Sci, 2017, 60: 063201
Li C Q, Li X B, Zhang J, et al. Analysis of airborne passive location precision based on multi-static cooperation. Modern Radar, 2017, 39: 11–14
Zhu H M, Wang H Y, Sun S Y. Research on error correction method of single UAV based on Monte Carlo. Sci Tech Eng, 2017, 17: 255–259
Esmailifar S M, Saghafi F. Cooperative localization of marine targets by UAVs. Mech Syst Signal Process, 2017, 87: 23–42
Lee W, Bang H, Leeghim H. Cooperative localization between small UAVs using a combination of heterogeneous sensors. Aerospace Sci Tech, 2013, 27: 105–111
Wang K, Ke Y, Chen B M. Autonomous reconfigurable hybrid tail-sitter UAV U-Lion. Sci China Inf Sci, 2017, 60: 033201
Yang K, An J P, Bu X Y, et al. Constrained total least-squares location algorithm using time-difference-of-arrival measurements. IEEE Trans Veh Technol, 2010, 59: 1558–1562
Melchor-Aguilar D, Niculescu S I. Computing non-fragile PI controllers for delay models of TCP/AQM networks. Int J Control, 2009, 82: 2249–2259
Zhu G, Feng D, Yan Z, et al. TOA localization algorithm using the linear-correction technique. J Xidian Univ, 2015, 42: 22–25, 32
Grewal M S, Weill L R, Andrews A P. Global Positioning Systems, Inertial Navigation, and Integration. Hoboken: John Wiley & Sons, Inc., 2007, 3: 383–384
Li W C, Wei P, Xiao X C. A robust TDOA-based location method and its performance analysis. Sci China Ser F-Inf Sci, 2009, 52: 876–882
Fan X, Younan N H, Taylor C D. A perturbation analysis of the regularized constrained total least squares. IEEE Trans Circ Syst II, 1996, 43: 140–142
This work was supported by National Natural Science Foundation of China (Grant No. 61473229).
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Qu, Y., Zhang, F., Wu, X. et al. Cooperative geometric localization for a ground target based on the relative distances by multiple UAVs. Sci. China Inf. Sci. 62, 10204 (2019). https://doi.org/10.1007/s11432-018-9579-3
- unmanned aerial vehicle
- relative distance
- cooperative localization
- location effectiveness analysis
- feasible regions